Search results for: family ICT learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9991

Search results for: family ICT learning

7171 Australian Football Supporters Engagement Patterns; Manchester United vs a-League

Authors: Trevor R. Higgins, Ben Lopez

Abstract:

Australian football fans have a tendency to indulge in foreign football clubs, often assigning a greater value to foreign clubs, in preference to the Australian National football competition; the A-League. There currently exists a gap in the knowledge available in relation to football fans in Australia, their engagement with foreign football teams and the impact that this may have with their engagement with A-League. The purpose of this study was to compare the engagement of the members of the Manchester United Supporters Club - Australia (MUSC-Aus) with Manchester United and the A-League. An online survey was implemented to gather the relevant data from members of the MUSC-Aus. Results from completed surveys were collected, and analyzed in relation to engagement levels with Manchester United and the A-League. Members of MUSC-Aus who responded to the survey were predominantly male (94%) and born in Australia (46%), England (25%), Ireland (7%), were greatly influenced in their choice of Manchester United by family (43%) and team history (16%), whereas location was the overwhelming influence in supporting the A-League (88%). Importantly, there was a reduced level of engagement in the A-League on two accounts. Firstly, only 64% of MUSC-Aus engaged with the A-League, reporting perceptions of low standard as the major reason (50%). Secondly, MUSC-Aus members who engaged in the A-League reported reduced engagement in the A-League, identified through spending patterns. MUSC-Aus members’ expenditure on Manchester United engagement was 400% greater than expenditure on A-League engagement. Furthermore, additional survey responses indicated that the level of commitment towards the A-League overall was less than Manchester United. The greatest impact on fan engagement in the A-League by MUSC-Aus can be attributed to several primary factors; family support, team history and perceptions to on-field performance and quality of players. Currently, there is little that can be done in regards to enhancing family and history as the A-League is still in its infancy. Therefore, perceptions of on-field performances and player quality should be addressed. Introducing short-term international marquee contracts to A-League rosters, across the entire competition, may provide the platform to raise the perception of the A-League player quality with minimal impact on local player development. In addition, a national marketing campaign promoting the success of A-League clubs in the ACL, as well as promoting the skill on display in the A-League may address the negative association with the standard of the A-League competition.

Keywords: engagement, football, perceptions of performance, team

Procedia PDF Downloads 277
7170 Comparative Outlook of Teacher Education in Nigeria and India

Authors: Muhammad Badamasi Abdullahi

Abstract:

Teacher education, both pre- and in-service programs, is offered in many countries of the world by different teacher education institutions as declared in the Policies on Education of the countries. However, differences exist from one country to another as a result of some factors peculiar to them. Notwithstanding, there also exist similarities among them in regard to teacher education. This paper is expected to dig into teacher education programs in Nigeria and India so that areas of similarities and differences would be highlighted as well as provide a venue for possible recommendation of both countries to learn from one another. All this is directed towards providing a no -border approach in enhancing effective teaching and learning.

Keywords: teacher education, teaching and learning, pre-service, in-service

Procedia PDF Downloads 378
7169 Developing Educator Cultural Awareness through Critically Reflective Professional Learning Community Collaboration

Authors: Brooke A. Moore

Abstract:

Developing teachers’ cultural awareness ensures schools are culturally responsive and socially just for diverse and exceptional students. An ideology of ‘normal’ exists in schools, creating boundaries where some students belong and others are marginalized based on difference. It is important that teacher preparation work to create democratic classrooms where teachers foster tolerance of difference and promote critical thinking and social justice. This paper outlines a framework for developing educator cultural awareness through the use of critically reflective professional learning communities (PLCs) drawing from the research on teacher critical reflection, collaborative PLCs, and Engeström’s theory of expansive learning. A case study using the framework was conducted with ten practicing teachers. Participants read and reflected on critical literature to make visible unexamined beliefs, engaged in conversations that pushed them to reflect more deeply and project forward new ideas, and set goals for acting as agents of change in their schools.

Keywords: cultural and linguistic diversity, diversity, special education, teacher beliefs

Procedia PDF Downloads 245
7168 Building Tutor and Tutee Pedagogical Agents to Enhance Learning in Adaptive Educational Games

Authors: Ogar Ofut Tumenayu, Olga Shabalina

Abstract:

This paper describes the application of two types of pedagogical agents’ technology with different functions in an adaptive educational game with the sole aim of improving learning and enhancing interactivities in Digital Educational Games (DEG). This idea could promote the elimination of some problems of DEG, like isolation in game-based learning, by introducing a tutor and tutee pedagogical agents. We present an analysis of a learning companion interacting in a peer tutoring environment as a step toward improving social interactions in the educational game environment. We show that tutor and tutee agents use different interventions and interactive approaches: the tutor agent is engaged in tracking the learner’s activities and inferring the learning state, while the tutee agent initiates interactions with the learner at the appropriate times and in appropriate manners. In order to provide motivation to prevent mistakes and clarity a game task, the tutor agent uses the help dialog tool to provide assistance, while the tutee agent provides collaboration assistance by using the hind tool. We presented our idea on a prototype game called “Pyramid Programming Game,” a 2D game that was developed using Libgdx. The game's Pyramid component symbolizes a programming task that is presented to the player in the form of a puzzle. During gameplay, the Agents can instruct, direct, inspire, and communicate emotions. They can also rapidly alter the instructional pattern in response to the learner's performance and knowledge. The pyramid must be effectively destroyed in order to win the game. The game also teaches and illustrates the advantages of utilizing educational agents such as TrA and TeA to assist and motivate students. Our findings support the idea that the functionality of a pedagogical agent should be dualized into an instructional and learner’s companion agent in order to enhance interactivity in a game-based environment.

Keywords: tutor agent, tutee agent, learner’s companion interaction, agent collaboration

Procedia PDF Downloads 62
7167 Cultural Stereotypes in EFL Classrooms and Their Implications on English Language Procedures in Cameroon

Authors: Eric Enongene Ekembe

Abstract:

Recent calls on EFL teaching posit the centrality of context factors and argue for a correlation between effectiveness in teaching with the learners’ culture in the EFL classroom. Context is not everything; it is defined with indicators of learners’ cultural artifacts and stereotypes in meaningful interactions in the language classroom. In keeping with this, it is difficult to universalise pedagogic procedures given that appropriate procedures are context-sensitive- and contexts differ. It is necessary to investigate what counts as cultural specificities or stereotypes of specific learners to reflect on how different language learning contexts affect or are affected by English language teaching procedures, most especially in under-represented cultures, which have appropriated the English language. This paper investigates cultural stereotypes of EFL learners in the culturally diverse Cameroon to examine how they mediate teaching and learning. Data collected on mixed-method basis from 83 EFL teachers and 1321 learners in Cameroon reveal a strong presence of typical cultural artifacts and stereotypes. Statistical analysis and thematic coding demonstrate that teaching procedures in place were insensitive to the cultural artifacts and stereotypes, resulting in trending tension between teachers and learners. The data equally reveal a serious contradiction between the communicative goals of language teaching and learning: what teachers held as effective teaching was diametrically opposed to success in learning. In keeping with this, the paper argues for a ‘decentred’ teacher preparation in Cameroon that is informed by systemic learners’ feedback. On this basis, applied linguistics has the urgent task of exploring dimensions of what actually counts as contextualized practice in ELT.

Keywords: cultural stereotypes, EFL, implications, procedures

Procedia PDF Downloads 122
7166 Predictive Machine Learning Model for Assessing the Impact of Untreated Teeth Grinding on Gingival Recession and Jaw Pain

Authors: Joseph Salim

Abstract:

This paper proposes the development of a supervised machine learning system to predict the consequences of untreated bruxism (teeth grinding) on gingival (gum) recession and jaw pain (most often bilateral jaw pain with possible headaches and limited ability to open the mouth). As a general dentist in a multi-specialty practice, the author has encountered many patients suffering from these issues due to uncontrolled bruxism (teeth grinding) at night. The most effective treatment for managing this problem involves wearing a nightguard during sleep and receiving therapeutic Botox injections to relax the muscles (the masseter muscle) responsible for grinding. However, some patients choose to postpone these treatments, leading to potentially irreversible and costlier consequences in the future. The proposed machine learning model aims to track patients who forgo the recommended treatments and assess the percentage of individuals who will experience worsening jaw pain, gingival (gum) recession, or both within a 3-to-5-year timeframe. By accurately predicting these outcomes, the model seeks to motivate patients to address the root cause proactively, ultimately saving time and pain while improving quality of life and avoiding much costlier treatments such as full-mouth rehabilitation to help recover the loss of vertical dimension of occlusion due to shortened clinical crowns because of bruxism, gingival grafts, etc.

Keywords: artificial intelligence, machine learning, predictive insights, bruxism, teeth grinding, therapeutic botox, nightguard, gingival recession, gum recession, jaw pain

Procedia PDF Downloads 84
7165 A Phishing Email Detection Approach Using Machine Learning Techniques

Authors: Kenneth Fon Mbah, Arash Habibi Lashkari, Ali A. Ghorbani

Abstract:

Phishing e-mails are a security issue that not only annoys online users, but has also resulted in significant financial losses for businesses. Phishing advertisements and pornographic e-mails are difficult to detect as attackers have been becoming increasingly intelligent and professional. Attackers track users and adjust their attacks based on users’ attractions and hot topics that can be extracted from community news and journals. This research focuses on deceptive Phishing attacks and their variants such as attacks through advertisements and pornographic e-mails. We propose a framework called Phishing Alerting System (PHAS) to accurately classify e-mails as Phishing, advertisements or as pornographic. PHAS has the ability to detect and alert users for all types of deceptive e-mails to help users in decision making. A well-known email dataset has been used for these experiments and based on previously extracted features, 93.11% detection accuracy is obtainable by using J48 and KNN machine learning techniques. Our proposed framework achieved approximately the same accuracy as the benchmark while using this dataset.

Keywords: phishing e-mail, phishing detection, anti phishing, alarm system, machine learning

Procedia PDF Downloads 333
7164 GA3C for Anomalous Radiation Source Detection

Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

Abstract:

In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

Procedia PDF Downloads 109
7163 Clinical Feature Analysis and Prediction on Recurrence in Cervical Cancer

Authors: Ravinder Bahl, Jamini Sharma

Abstract:

The paper demonstrates analysis of the cervical cancer based on a probabilistic model. It involves technique for classification and prediction by recognizing typical and diagnostically most important test features relating to cervical cancer. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases. The combination of the conventional statistical and machine learning tools is applied for the analysis. Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Keywords: cervical cancer, recurrence, no recurrence, probabilistic, classification, prediction, machine learning

Procedia PDF Downloads 357
7162 Is There a Group of "Digital Natives" at Secondary Schools?

Authors: L. Janská, J. Kubrický

Abstract:

The article describes a research focused on the influence of the information and communication technology (ICT) on the pupils' learning. The investigation deals with the influences that distinguish between the group of pupils influenced by ICT and the group of pupils not influenced by ICT. The group influenced by ICT should evince a different approach in number of areas (in managing of two and more activities at once, in a quick orientation and searching for information on the Internet, in an ability to quickly and effectively assess the data sources, in the assessment of attitudes and opinions of the other users of the network, in critical thinking, in the preference to work in teams, in the sharing of information and personal data via the virtual social networking, in insisting on the immediate reaction on their every action etc.).

Keywords: ICT influence, digital natives, pupil´s learning

Procedia PDF Downloads 287
7161 Effect of Diet and Life Style Modification to Control the Plasma Glucose Level in the 60 Patients of Gestational Diabetes Mellitus

Authors: Vivek Saxena, Shreshtha Saxena

Abstract:

Background: Gestational diabetes mellitus (GDM) is defined as impaired glucose tolerance first recognized during pregnancy. Uncontrolled or untreated GDM is associated with various adverse outcomes to the maternal and fetal health. Overt diabetes mellitus may also develop in such patients. It is universally accepted fact that first and foremost management to treat GDM is dietary control and lifestyle modification even before starting any oral hypoglycemic agent (OHA) or insulin. So, proper dietary management and little changes in the patient’s lifestyle are very effective for reducing her plasma glucose level. Objectives: Proper counselling of the patients and flexibility in their lifestyle and diet can effectively control the plasma glucose level in GDM patients. Methods: Total 60 GDM patients of age > 18 years were taken. We had three counselling sessions with the patient and other members of the family like husband, parents, and in-laws at different intervals, discussed their lifestyle and diet pattern, helped them to eliminate the factors those had an adverse effect on plasma glucose level and promoted them to acquire a healthy lifestyle. We have counselled the patient and her family member separately and then together also. They have explained how increased plasma glucose level can be effectively controlled with the little modification in their diet and routine activities. They were also taught to remain stress-free during their rest of antenatal period. We have excluded the patients from our study who were diabetic before pregnancy and patients with other comorbid illnesses like hypothyroidism and valvular heart disease. Results and conclusions: Results were very rewarding as patients could acquire a lifestyle of their choice. They were happy because extra pill burden was not there. All the 60 patients were normoglycemic in remaining antenatal period, 48 patients were delivered normally and 12 patients underwent cesarean section due to various reasons.Regular counselling of the patients regarding their disease and little alterations in diet and lifestyle controlled the plasma glucose level much effectively. The things were more easier and effective when we included other family members during our counselling session because they play a major role in patient’s day to day activity and influence her life.

Keywords: dietary management, gestational diabetes mellitus, impaired glucose tolerance, oral hypoglycemic agent, pregnancy

Procedia PDF Downloads 158
7160 Gamification Teacher Professional Development: Engaging Language Learners in STEMS through Game-Based Learning

Authors: Karen Guerrero

Abstract:

Kindergarten-12th grade teachers engaged in teacher professional development (PD) on game-based learning techniques and strategies to support teaching STEMSS (STEM + Social Studies with an emphasis on geography across the curriculum) to language learners. Ten effective strategies have supported teaching content and language in tandem. To provide exiting teacher PD on summer and spring breaks, gamification has integrated these strategies to engage linguistically diverse student populations to provide informal language practice while students engage in the content. Teachers brought a STEMSS lesson to the PD, engaged in a wide variety of games (dice, cards, board, physical, digital, etc.), critiqued the games based on gaming elements, then developed, brainstormed, presented, piloted, and published their game-based STEMSS lessons to share with their colleagues. Pre and post-surveys and focus groups were conducted to demonstrate an increase in knowledge, skills, and self-efficacy in using gamification to teach content in the classroom. Provide an engaging strategy (gamification) to support teaching content and language to linguistically diverse students in the K-12 classroom. Game-based learning supports informal language practice while developing academic vocabulary utilized in the game elements/content focus, building both content knowledge through play and language development through practice. The study also investigated teacher's increase in knowledge, skills, and self-efficacy in using games to teach language learners. Mixed methods were used to investigate knowledge, skills, and self-efficacy prior to and after the gamification teacher training (pre/post) and to understand the content and application of developing and utilizing game-based learning to teach. This study will contribute to the body of knowledge in applying game-based learning theories to the K-12 classroom to support English learners in developing English skills and STEMSS content knowledge.

Keywords: gamification, teacher professional development, STEM, English learners, game-based learning

Procedia PDF Downloads 82
7159 An Investigation on Physics Teachers’ Views Towards Context Based Learning Approach

Authors: Medine Baran, Abdulkadir Maskan, Mehmet Ikbal Yetişir, Mukadder Baran, Azmi Türkan, Şeyma Yaşar

Abstract:

The purpose of this study was to determine the views of physics teachers from several secondary schools in Turkey towards context-based learning approach. In the study, the context-based learning opinion questionnaire developed by the researchers for use as the data collection tool was piloted with 250 physics teachers. The questionnaire examined by the researchers and field experts was initially made up of 53 items. Following the evaluation process of the questionnaire, it included 37 items. In this way, the reliability and validity process of the measurement tool was completed. In the end, the finalized questionnaire was applied to 144 physics teachers from several secondary schools in different cities in Turkey (F:73, M:71). In the study, the participants were determined based on ease of reaching them. The results revealed no remarkable difference between the views of the physics teachers with respect to their gender, region and school. However, when the items in the questionnaire were considered, it was found that the participants interestingly agreed on some of the choices in the items. Depending on this, it was found that there were high levels of differences between the frequencies of those who agreed and those who disagreed with the 16 items in the questionnaire. Therefore, as the following phase of the present study, further research has been planned using the same questions. Based on these questions, which received opposite responses, physics teachers will be asked for their views about the results of the study using the interview technique, one of qualitative research techniques. In this way, the results will be evaluated both by the researchers and by the participants, and the problems and difficulties will be determined. As a result, related suggestions can be put forward.

Keywords: context bases learning, physics teachers, views

Procedia PDF Downloads 371
7158 Integrated Education at Jazan University: Budding Hope for Employability

Authors: Jayanthi Rajendran

Abstract:

Experience is what makes a man perfect. Though we tend to learn many a different things in life through practice still we need to go an extra mile to gain experience which would be profitable only when it is integrated with regular practice. A clear phenomenal idea is that every teacher is a learner. The centralized idea of this paper would focus on the integrated practices carried out among the students of Jizan University which enhances learning through experiences. Integrated practices like student-directed activities, balanced curriculum, phonological based activities and use of consistent language would enlarge the vision and mission of students to earn experience through learning. Students who receive explicit instruction and guidance could practice the skills and strategies through student-directed activities such as peer tutoring and cooperative learning. The second effective practice is to use consistent language. Consistent language provides students a model for talking about the new concepts which also enables them to communicate without hindrances. Phonological awareness is an important early reading skill for all students. Students generally have phonemic awareness in their home language can often transfer that knowledge to a second language. And also a balanced curriculum requires instruction in all the elements of reading. Reading is the most effective skill when both basic and higher-order skills are included on a daily basis. Computer based reading and listening skills will empower students to understand a language in a better way. English language learners can benefit from sound reading instruction even before they are fully proficient in English as long as the instruction is comprehensible. Thus, if students have to be well equipped in learning they should foreground themselves in various integrated practices through multifarious experience for which teachers are moderators and trainers. This type of learning prepares the students for a constantly changing society which helps them to meet the competitive world around them for better employability fulfilling the vision and mission of the institution.

Keywords: consistent language, employability, phonological awareness, balanced curriculum

Procedia PDF Downloads 397
7157 Laban Movement Analysis Using Kinect

Authors: Bernstein Ran, Shafir Tal, Tsachor Rachelle, Studd Karen, Schuster Assaf

Abstract:

Laban Movement Analysis (LMA), developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Many applications that use motion capture data might be significantly leveraged if the Laban qualities will be recognized automatically. This paper presents an automated recognition method of Laban qualities from motion capture skeletal recordings and it is demonstrated on the output of Microsoft’s Kinect V2 sensor.

Keywords: Laban movement analysis, multitask learning, Kinect sensor, machine learning

Procedia PDF Downloads 335
7156 The Negative Relational Outcomes Bullying Has On Youth with Disabilities

Authors: Kaycee Bills

Abstract:

Studies have demonstrated that middle and high school students with disabilities are more likely to experience bullying than other student groups. The high rates of bullying victimization observed among youth with disabilities can result in severe socio-emotional consequences. These socio-emotional consequences often manifest in detrimental impacts on the students’ personal relationships. Past studies have indicated that participating in extracurricular athletic activities can have several socio-emotional benefits for students with disabilities. Given the findings of past studies demonstrating the positive relationship between mental health and participation in sports among students with disabilities, it is possible that participating in athletics could have a moderating relationship on the severity of the impact that bullying has on a student’s relationships with family and friends. Using the National Crime Victimization Survey/School Crime Supplement (NCVS/SCS), this study employs an ordinal logistic regression to determine if participation in extracurricular athletic activities mitigates the damaging impact bullying has on the personal relationships with friends and family among students who have disabilities. This study identified statistically significant results suggesting that students with disabilities who participate in athletics reported reduced levels of negative personal relationships resulting from bullying compared to their peers who did not participate in athletics.

Keywords: disability, inclusion, bullying, relationships

Procedia PDF Downloads 165
7155 Human Resources and Business Result: An Empirical Approach Based on RBV Theory

Authors: Xhevrie Mamaqi

Abstract:

Organization capacity learning is a process referring to the sum total of individual and collective learning through training programs, experience and experimentation, among others. Today, in-business ongoing training is one of the most important strategies for human capital development and it is crucial to sustain and improve workers’ knowledge and skills. Many organizations, firms and business are adopting a strategy of continuous learning, encouraging employees to learn new skills continually to be innovative and to try new processes and work in order to achieve a competitive advantage and superior business results. This paper uses the Resource Based View and Capacities (RBV) approach to construct a hypothetical relationships model between training and business results. The test of the model is applied on transversal data. A sample of 266 business of Spanish sector service has been selected. A Structural Equation Model (SEM) is used to estimate the relationship between ongoing training, represented by two latent dimension denominated Human and Social Capital resources and economic business results. The coefficients estimated have shown the efficient of some training aspects explaining the variation in business results.

Keywords: business results, human and social capital resources, training, RBV theory, SEM

Procedia PDF Downloads 295
7154 Review of Studies on Agility in Knowledge Management

Authors: Ferdi Sönmez, Başak Buluz

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Agility in Knowledge Management (AKM) tries to capture agility requirements and their respective answers within the framework of knowledge and learning for organizations. Since it is rather a new construct, it is difficult to claim that it has been sufficiently discussed and analyzed in practical and theoretical realms. Like the term ‘agile learning’, it is also commonly addressed in the software development and information technology fields and across the related areas where those technologies can be applied. The organizational perspective towards AKM, seems to need some more time to become scholarly mature. Nevertheless, in the literature one can come across some implicit usages of this term occasionally. This research is aimed to explore the conceptual background of agility in KM, re-conceptualize it and extend it to business applications with a special focus on e-business.

Keywords: knowledge management, agility requirements, agility, knowledge

Procedia PDF Downloads 257
7153 3D Plant Growth Measurement System Using Deep Learning Technology

Authors: Kazuaki Shiraishi, Narumitsu Asai, Tsukasa Kitahara, Sosuke Mieno, Takaharu Kameoka

Abstract:

The purpose of this research is to facilitate productivity advances in agriculture. To accomplish this, we developed an automatic three-dimensional (3D) recording system for growth of field crops that consists of a number of inexpensive modules: a very low-cost stereo camera, a couple of ZigBee wireless modules, a Raspberry Pi single-board computer, and a third generation (3G) wireless communication module. Our system uses an inexpensive Web stereo camera in order to keep total costs low. However, inexpensive video cameras record low-resolution images that are very noisy. Accordingly, in order to resolve these problems, we adopted a deep learning method. Based on the results of extended period of time operation test conducted without the use of an external power supply, we found that by using Super-Resolution Convolutional Neural Network method, our system could achieve a balance between the competing goals of low-cost and superior performance. Our experimental results showed the effectiveness of our system.

Keywords: 3D plant data, automatic recording, stereo camera, deep learning, image processing

Procedia PDF Downloads 271
7152 Quality of Life Among People with Mental Illness Attending a Psychiatric Outpatient Clinic in Ethiopia: A Structural Equation Model

Authors: Wondale Getinet Alemu, Lillian Mwanri, Clemence Due, Telake Azale, Anna Ziersch

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Background: Mental illness is one of the most severe, chronic, and disabling public health problems that affect patients' Quality of life (QoL). Improving the QoL for people with mental illness is one of the most critical steps in stopping disease progression and avoiding complications of mental illness. Therefore, we aimed to assess the QoL and its determinants in patients with mental illness in outpatient clinics in Northwest Ethiopia in 2023. Methods: A facility-based cross-sectional study was conducted among people with mental illness in an outpatient clinic in Ethiopia. The sampling interval was decided by dividing the total number of study participants who had a follow-up appointment during the data collection period (2400) by the total sample size of 638, with the starting point selected by lottery method. The interviewer-administered WHOQOL BREF-26 tool was used to measure the QoL of people with mental illness. The domains and Health-Related Quality of Life (HRQoL) were identified. The indirect and direct effects of variables were calculated using structural equation modeling with SPSS-28 and Amos-28 software. A p-value of < 0.05 and a 95% CI were used to evaluate statistical significance. Results: A total of 636 (99.7%) participants responded and completed the WHOQOL-BREF questionnaire. The mean score of overall HRQoL of people with mental illness in the outpatient clinic was (49.6 ± 10 Sd). The highest QoL was found in the physical health domain (50.67 ±9.5 Sd), and the lowest mean QoL was found in the psychological health domain (48.41±10 Sd). Rural residents, drug nonadherence, suicidal ideation, not getting counseling, moderate or severe subjective severity, the family does not participate in patient care, and a family history of mental illness had an indirect negative effect on HRQoL. Alcohol use and psychological health domain had a direct positive effect on QoL. Furthermore, objective severity of illness, having low self-esteem, and having a history of mental illness in the family had both direct and indirect effects on QoL. Furthermore, sociodemographic factors (residence, educational status, marital status), social support-related factors (self-esteem, family not participating in patient care), substance use factors (alcohol use, tobacco use,) and clinical factors (objective and subjective severity of illness, not getting counseling, suicidal ideation, number of episodes, comorbid illness, family history of mental illness, poor drug adherence) directly and indirectly affected QoL. Conclusions: In this study, the QoL of people with mental illness was poor, with the psychological health domain being the most affected. Sociodemographic factors, social support-related factors, drug use factors, and clinical factors directly and indirectly, affect QoL through the mediator variables of physical health domains, psychological health domains, social relation health domains, and environmental health domains. In order to improve the QoL of people with mental illnesses, we recommend that emphasis be given to addressing the scourge of mental health, including the development of policy and practice drivers that address the above-identified factors.

Keywords: quality of life, mental wellbeing, mental illness, mental disorder, Ethiopia

Procedia PDF Downloads 71
7151 Challenge in Teaching Physics during the Pandemic: Another Way of Teaching and Learning

Authors: Edson Pierre, Gustavo de Jesus Lopez Nunez

Abstract:

The objective of this work is to analyze how physics can be taught remotely through the use of platforms and software to attract the attention of 2nd-year high school students at Colégio Cívico Militar Professor Carmelita Souza Dias and point out how remote teaching can be a teaching-learning strategy during the period of social distancing. Teaching physics has been a challenge for teachers and students, permeating common sense with the great difficulty of teaching and learning the subject. The challenge increased in 2020 and 2021 with the impact caused by the new coronavirus pandemic (Sars-Cov-2) and its variants that have affected the entire world. With these changes, a new teaching modality emerged: remote teaching. It brought new challenges and one of them was promoting distance research experiences, especially in physics teaching, since there are learning difficulties and it is often impossible for the student to relate the theory observed in class with the reality that surrounds them. Teaching physics in schools faces some difficulties, which makes it increasingly less attractive for young people to choose this profession. Bearing in mind that the study of physics is very important, as it puts students in front of concrete and real situations, situations that physical principles can respond to, helping to understand nature, nourishing and nurturing a taste for science. The use of new platforms and software, such as PhET Interactive Simulations from the University of Colorado at Boulder, is a virtual laboratory that has numerous simulations of scientific experiments, which serve to improve the understanding of the content taught practically, facilitating student learning and absorption of content, being a simple, practical and free simulation tool, attracts more attention from students, causing them to acquire greater knowledge about the subject studied, or even a quiz, bringing certain healthy competitiveness to students, generating knowledge and interest in the themes used. The present study takes the Theory of Social Representations as a theoretical reference, examining the content and process of constructing the representations of teachers, subjects of our investigation, on the evaluation of teaching and learning processes, through a methodology of qualitative. The result of this work has shown that remote teaching was really a very important strategy for the process of teaching and learning physics in the 2nd year of high school. It provided greater interaction between the teacher and the student. Therefore, the teacher also plays a fundamental role since technology is increasingly present in the educational environment, and he is the main protagonist of this process.

Keywords: physics teaching, technologies, remote learning, pandemic

Procedia PDF Downloads 59
7150 Data Mining in Medicine Domain Using Decision Trees and Vector Support Machine

Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

Procedia PDF Downloads 550
7149 Multilevel Modelling of Modern Contraceptive Use in Nigeria: Analysis of the 2013 NDHS

Authors: Akiode Ayobami, Akiode Akinsewa, Odeku Mojisola, Salako Busola, Odutolu Omobola, Nuhu Khadija

Abstract:

Purpose: Evidence exists that family planning use can contribute to reduction in infant and maternal mortality in any country. Despite these benefits, contraceptive use in Nigeria still remains very low, only 10% among married women. Understanding factors that predict contraceptive use is very important in order to improve the situation. In this paper, we analysed data from the 2013 Nigerian Demographic and Health Survey (NDHS) to better understand predictors of contraceptive use in Nigeria. The use of logistics regression and other traditional models in this type of situation is not appropriate as they do not account for social structure influence brought about by the hierarchical nature of the data on response variable. We therefore used multilevel modelling to explore the determinants of contraceptive use in order to account for the significant variation in modern contraceptive use by socio-demographic, and other proximate variables across the different Nigerian states. Method: This data has a two-level hierarchical structure. We considered the data of 26, 403 married women of reproductive age at level 1 and nested them within the 36 states and the Federal Capital Territory, Abuja at level 2. We modelled use of modern contraceptive against demographic variables, being told about FP at health facility, heard of FP on TV, Magazine or radio, husband desire for more children nested within the state. Results: Our results showed that the independent variables in the model were significant predictors of modern contraceptive use. The estimated variance component for the null model, random intercept, and random slope models were significant (p=0.00), indicating that the variation in contraceptive use across the Nigerian states is significant, and needs to be accounted for in order to accurately determine the predictors of contraceptive use, hence the data is best fitted by the multilevel model. Only being told about family planning at the health facility and religion have a significant random effect, implying that their predictability of contraceptive use varies across the states. Conclusion and Recommendation: Results showed that providing FP information at the health facility and religion needs to be considered when programming to improve contraceptive use at the state levels.

Keywords: multilevel modelling, family planning, predictors, Nigeria

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7148 Form of Social Quality Moving Process of Suburb Communities in a Changing World

Authors: Supannee Chaiumporn

Abstract:

This article is to introduce the meaning and form of social quality moving process as indicated by members of two suburb communities with different social and cultural contexts. The form of social quality moving process is very significant for the community and social development, because it will make the people living together with sustainable happiness. This is a qualitative study involving 30 key-informants from two suburb communities. Data were collected though key-informant interviews, and analyzed using logical content description and descriptive statistics. This research found that on the social quality component, the people in both communities stressed the procedure for social quality-making. This includes the generousness, sharing and assisting among people in the communities. These practices helped making people to live together with sustainable happiness. Living as a family or appear to be a family is the major social characteristic of these two communities. This research also found that form of social quality’s moving process of both communities stress relation of human and nature; “nature overpower humans” paradigm and influence of religious doctrine that emphasizes relations among humans. Both criteria make the form of social’s moving process simple, adaptive to nature and caring for opinion sharing and understanding among each other before action. This form of social quality’s moving process is composed of 4 steps; (1) awareness building, (2) motivation to change, (3) participation from every party concerned (4) self-reliance.

Keywords: social quality, form of social quality moving process, happiness, different social and cultural context

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7147 A New Learning Automata-Based Algorithm to the Priority-Based Target Coverage Problem in Directional Sensor Networks

Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

Abstract:

Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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7146 Rural School English Teacher Motivational Practice on Facilitating Student Motivation

Authors: Hsiao-Wen Hsu

Abstract:

It is generally believed that the teacher’s use of motivational strategies can enhance student motivation, especially in a place like Taiwan where teacher usually dominates student EFL learning. However, only little empirical studies support this claim. This study examined the connection between teachers’ use of motivational teaching practice and observed student motivated behavior in rural junior high schools in Taiwan. The use of motivational strategies by 12 teachers in five recognized rural junior high schools was investigated observed using a classroom observation instrument, the Motivation Orientation of Language Teaching. Meanwhile, post-lesson teacher evaluations accomplished by both the researcher and the teacher were functioning as part of the measure of teacher motivational practice. The data collected through observation scheme follows the real-time coding principle to examine observable teacher motivational practice and learner motivated behaviors. The results support the previous research findings that teachers’ use of motivational strategies is associated with the student motivated behaviors as well as the students’ level of motivation regarding English learning.

Keywords: English learning, motivational strategies, student motivation, teacher motivational practices

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7145 Teachers' Design and Implementation of Collaborative Learning Tasks in Higher Education

Authors: Bing Xu, Kerry Lee, Jason M. Stephen

Abstract:

Collaborative learning (CL) has been regarded as a way to facilitate students to gain knowledge and improve social skills. In China, lecturers in higher education institutions have commonly adopted CL in their daily practice. However, such a strategy could not be effective when it is designed and applied in an inappropriate way. Previous research hardly focused on how CL was applied in Chinese universities. This present study aims to gain a deep understanding of how Chinese lecturers design and implement CL tasks. The researchers interviewed ten lecturers from different faculties in various universities in China and usedGroup Learning Activity Instructional Design (GLAID) framework to analyse the data. We found that not all lecturers pay enough attention to eight essential components (proposed by GLAID) when they designed CL tasks, especially the components of Structure and Guidance. Meanwhile, only a small part of lecturers made formative assessment to help students improve learning. We also discuss the strengths and limitations and CL design and further provide suggestions to the lecturers who intend to use CL in class. Research Objectives: The aims of the present research are threefold. We intend to 1) gain a deep understanding of how Chinese lecturers design and implement collaborative learning (CL) tasks, 2) find strengths and limitations of CL design in higher education, and 3) give suggestions about how to improve the design and implement. Research Methods: This research adopted qualitative methods. We applied the semi-structured interview method to interview ten Chinese lecturers about how they designed and implemented CL tasks in their courses. There were 9 questions in the interview protocol focusing on eight components of GLAID. Then, underpinning the GLAID framework, we utilized the coding reliability thematic analysis method to analyse the research data. The coding work was done by two PhD students whose research fields are CL, and the Cohen’s Kappa was 0.772 showing the inter-coder reliability was good. Contribution: Though CL has been commonly adopted in China, few studies have paid attention to the details about how lecturers designed and implemented CL tasks in practice. This research addressed such a gap and found not lecturers were aware of how to design CL and felt it difficult to structure the task and guide the students on collaboration, and further ensure student engagement in CL. In summary, this research advocates for teacher training; otherwise, students may not gain the expected learning outcomes.

Keywords: collaborative learning, higher education, task design, GLAID framework

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7144 Development of National Education Policy-2020 Aligned Student-Centric-Outcome-Based-Curriculum of Engineering Programmes of Polytechnics in India: Faculty Preparedness and Challenges Ahead

Authors: Jagannath P. Tegar

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The new National Education Policy (NEP) 2020 of Govt. of India has envisaged a major overhaul of the education system of India, in particular, the revamping of the Curriculum of Higher Education. In this process, the faculty members of the Indian universities and institutions have a challenging role in developing the curriculum, which is a shift from the traditional (content-based) curriculum to a student-centric- outcome-based Curriculum (SC-OBC) to be implemented in all of the Universities and institutions. The efforts and initiatives on the design and implementation of SC-OBC are remarkable in the engineering and technical education landscape of the country, but it is still in its early stages and many more steps are needed for the successful adaptation in every level of Higher Education. The premier institute of Govt. of India (NITTTR, Bhopal) has trained and developed the capacity and capability among the teachers of Polytechnics on the design and development of Student Centric - Outcome Based Curriculum and also providing academic consultancy for reforming curriculum in line of NEP- 2020 envisions for the states such as Chhattisgarh, Bihar and Maharashtra to make them responsibly ready for such a new shift in Higher Education. This research-based paper is on three main aspects: 1) the level of acceptance and preparedness of teachers /faculty towards NEP-2020 and student-centred outcome-based learning. 2) the extent of implementing NEP-2020 and student-centered outcome-based learning at Indian institutions/ universities and 3) the challenges of implementing NEP-2020 and student-centered outcome-based learning outcome-based education in the Indian context. The paper content will inspire curriculum designers and developers to prepare SC-OBC that meets the specific needs of industry and society at large, which is intended in the NEP-2020 of Govt. of India

Keywords: outcome based curriculum, student centric learning, national education policy -2020, implementation of nep-2020. outcome based learning, higher education curriculum

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7143 Factors Influencing Soil Organic Carbon Storage Estimation in Agricultural Soils: A Machine Learning Approach Using Remote Sensing Data Integration

Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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7142 A Comparison of Convolutional Neural Network Architectures for the Classification of Alzheimer’s Disease Patients Using MRI Scans

Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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